January 2021
Volume 10, Issue 1
Open Access
Articles  |   January 2021
Development of the Vision Impairment in Low Luminance Questionnaire
Author Affiliations & Notes
  • Susanne G. Pondorfer
    Department of Ophthalmology, University Hospital Bonn, Bonn, Germany
  • Jan H. Terheyden
    Department of Ophthalmology, University Hospital Bonn, Bonn, Germany
  • Helen Overhoff
    Forschungszentrum Jülich, Jülich, Germany
  • Jana Stasch-Bouws
    AMD-Netz e.V., Münster, Germany
  • Frank G. Holz
    Department of Ophthalmology, University Hospital Bonn, Bonn, Germany
  • Robert P. Finger
    Department of Ophthalmology, University Hospital Bonn, Bonn, Germany
  • Correspondence: Robert P. Finger, University of Bonn, Dept. of Ophthalmology, Ernst-Abbe-Str. 2, D-53127 Bonn, Germany. e-mail: robert.finger@ukbonn.de 
  • Footnotes
    *  SGP and JHT contributed equally to this work.
Translational Vision Science & Technology January 2021, Vol.10, 5. doi:https://doi.org/10.1167/tvst.10.1.5
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Susanne G. Pondorfer, Jan H. Terheyden, Helen Overhoff, Jana Stasch-Bouws, Frank G. Holz, Robert P. Finger; Development of the Vision Impairment in Low Luminance Questionnaire. Trans. Vis. Sci. Tech. 2021;10(1):5. doi: https://doi.org/10.1167/tvst.10.1.5.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose: The purpose of this study was to design and evaluate an instrument for assessing vision-related quality of life appropriate for the specific visual impairment characteristic for all stages of age-related macular degeneration (AMD), with a focus on the low luminance deficit in early/intermediate stages.

Methods: A standardized questionnaire was developed in three steps with participants with early, intermediate, and late AMD: (1) based on in-depth interviews (n = 19) and two focus group discussions (n = 5 each), content was developed followed by 2. (2) The questionnaire development using cognitive debriefing interviews (n = 3) and leading to a preliminary version of the questionnaire. (3) This version was then administered to 127 participants with early, intermediate, and late AMD. Psychometric properties, such as response category functioning (floor and ceiling effects) and targeting of item difficulty to patient ability of the pilot Vision Impairment in Low Luminance (VILL) questionnaire were evaluated using Rasch analysis.

Results: The preliminary VILL questionnaire consisted of 68 items with a 5-step response scale. Several items were removed based on floor/ceiling effects or misfit and a final pool of 37 items remained. The response scale was collapsed to four categories as one category was underutilized. The targeting of the instrument was good with minimal difference in person and item means (0.52 logits). Precision was also good with a person separation index of 3.55 and reliability of 0.93. There was evidence of multidimensionality (eigenvalue of the first contrast = 5.95) in the scale, which could be resolved by splitting the items into subscales including a reading, mobility, and emotional well-being subscale.

Conclusions: Individuals with AMD report difficulties with vision-related activities and functioning under visually challenging conditions at all stages of the disease. These aspects were considered when developing the 37-item VILL, which demonstrates promising psychometric characteristics. Further assessments of reliability and validity are warranted.

Translational Relevance: The VILL questionnaire is a new patient-reported outcome (PRO) measure developed for future use in AMD studies.

Introduction
Age-related macular degeneration (AMD) remains the most common cause of severe visual loss in all high-income countries and we currently lack both interventions to stop or delay onset and progression of early stages of AMD as well as clinical end points to evaluate such interventions in early stages of AMD (i.e. early and intermediate AMD).13 In early and intermediate AMD, patients usually perform well in standard high contrast, high luminance best-corrected visual acuity (BCVA) testing.4 However, the most widely used outcome measure in ophthalmic research is BCVA,5,6 which appears to be largely insensitive to the specific functional impairment in early and intermediate AMD.7,8 Common visual symptoms in early stages include problems seeing in dim light and at night911 and patients often report difficulties with low contrast and low luminance.9,12 Previous studies have shown that this vision impairment impacts activities of daily living, falls, and mobility, as well as emotional well-being,9,1315 and that self-reported night vision symptoms are associated with low luminance deficit (LLD).16 The degree of self-reported problems with night vision could be shown to predict both disease progression from early to late AMD as well as a loss of BCVA ≥ 3 lines over a period of 6 years.17,18 
In fact, patient-reported outcomes (PROs) are increasingly used to assess the impact of vision impairment from the patient's perspective, including patient-relevance of changes in retinal structure and functional testing also in a regulatory context.1921 Although many questionnaires for assessing vision-related quality of life (VRQOL) and functional ability are available, none have been specifically developed to include vision impairment characteristics of early stages of AMD following available regulatory guidelines.22,23 Existing measures, such as the Low Luminance Questionnaire (LLQ) or the Night Vision Questionnaire (NVQ), have been developed with patients with AMD but did not follow the US Food and Drug Administration's guidance on PRO development (e.g. including multilevel results of qualitative research to support the instrument's content validity) or have been developed as a generic measure of VRQOL derived from the National Eye Institute Visual Functioning Questionnaire 25 items (NEI-VFQ-25), respectively.9,17 
To enable the development of interventions with the goal to delay or stop onset and progression or reduce visual impairment in early and intermediate AMD, a PRO instrument developed in accordance with existing regulatory guidelines24 is needed to assess the subjective impact and relevance of specific impairment as perceived by patients across all stages of AMD. In order to fill this gap, we designed and evaluated the Vision Impairment in Low Luminance (VILL) questionnaire. 
Methods
Participants
All participants were adults (≥ 55 years) and were categorized into early, intermediate, or late AMD based on the Beckman classification system introduced by Ferris et al. based on a clinical assessment including multimodal retinal imaging by a retina specialist.25 Patients were recruited from outpatient clinics. The study was approved by the Institutional Review Board of the University of Bonn (approval ID: 130/16). All patients gave informed consent for study participation. The protocol followed the tenets of the Declaration of Helsinki. 
Phases of Instrument Development
The instrument was developed in three steps. In the first phase, content for questionnaire items was identified by reviewing existing instruments, including but not limited to the Functional Reading Independence Index (FRII),26 the Impact of Vision Impairment – Very Low Vision (IVI-VLV) questionnaire,27 the LLQ,9 the 10-item NVQ (NVQ-10),17 and the NEI-VFQ-25.28 Furthermore, 19 in-depth interviews as well as 2 focus groups discussions (FGDs) were conducted with patients with early, intermediate, or late AMD. Interviews and FGDs were conducted by a trained interviewer using an interview guideline. In-depth interviews were conducted either in person or by telephone, depending on participant preference. For FGDs, participants with similar levels of disease severity were grouped to foster social facilitation, a common approach in FGDs.29 Both in-depth interviews and FGDs were audiotaped and transcribed verbatim. Transcripts were examined using an inductive analytical approach. This is an iterative process, which involves broadly coding data into themes and subsequently continually revising these themes as further transcripts are analyzed until thematic saturation occurs. Data were analyzed qualitatively using NVivo (version 11; QSR International, Burlington, MA, USA) for structuring and visualization purposes.30 In the second phase, this content was used to develop a preliminary VILL questionnaire with 75 items and a five-step response scale ranging from “very” to “not at all” (items 1–32) and “always” to “never” (items 33–68). One additional response option captured whether items were applicable to participants (i.e.: “not applicable”). This was followed by cognitive debriefing interviews to ascertain unambiguous phrasing of items and response scales as well as appropriateness of content based on a standardized guideline and during which patients were encouraged to think aloud.31 In a third phase, the resulting 68 items pilot VILL was administered to 127 patients with early, intermediate, and late AMD. Best-corrected visual acuity (BCVA) of these patients was assessed according to the early treatment diabetic retinopathy study (ETDRS) method.32 
Psychometric properties of the pilot VILL questionnaire, such as response distribution per item (floor and ceiling effects) and targeting of item difficulty to participant ability, were determined using Rasch analysis. Supplementary Table S1 provides an overview of all items tested and the final items retained for the VILL. 
Psychometric Evaluation of the Pilot VILL
Rasch analysis is a psychometric method that mathematically describes the interaction between respondents and test items and applies a model that the pattern of participants’ responses should satisfy.27,33,34 It transforms ordinal scales into interval-level scales (expressed in logits). This allows to calculate item difficulty (item measure) in relation to person ability (person measure) by placing both in the same linear continuum.35,36 To assess the psychometric properties of the pilot VILL, we used the following criteria. 
Threshold Ordering: We assessed the response category threshold ordering to determine whether the categories used to rate VILL items are valid. Over- or underutilization of response categories and the ability of participants to discriminate between the response categories were assessed. Disordered thresholds, if evident, were addressed by collapsing categories.37,38 
Precision of the Instrument: The ability of the scale to discriminate between different levels strata of person ability was assessed using person separation index (PSI) and person reliability (PR) scores. Values of > 2.0 and > 0.8, respectively, were considered adequate and represented the capacity of the scale to distinguish three levels of person ability.39,40 
Unidimensionality: Unidimensionality describes the ability of a scale to measure a single underlying trait and whether the items’ “fit” the underlying trait which was assessed twofold. First, we determined how well each item “fits” or “misfits” the underlying trait through an “infit” mean square standardized residuals (MNSQ) statistic.41 An infit MNSQ value of 1 is ideal and up to 1.3 is acceptable. High fit values are regarded as misfitting (noisy and erratic) and values below 0.7 as overfitting (muted).39 Second, we conducted a principal component analysis (PCA) of the residuals in order to test for local independence. The PCA of residuals for the first factor should explain at least 50% of the variance and the first contrast of residuals should be < 2.5 eigenvalue.42,43 
Targeting: The targeting of the instrument (i.e. how well item difficulty corresponds to the person’s ability), was determined by inspecting the person-item map and calculating the difference between person and item mean logits. A difference of > 1.0 logits indicates that the difficulty of the respective item does not adequately target the ability of the sample.38,44 
Differential Item Functioning (DIF): Each item was assessed for DIF, which is a statistical method for detecting whether sample subgroups (e.g. gender and age groups) respond systematically different to certain items, despite having a similar underlying ability. A DIF contrast of > 1.0 logits is notable and suggests that the item may be biased for some participant subgroups. We assessed DIF for gender and age groups < 75 years and ≥ 75 years (based on the median age of the sample). Only significant DIF values (P < 0.05) were reported. 
Rasch analysis was performed using commercial software (version 3.92.1.2; Winsteps Software, Chicago, IL).42 The Andrich rating scale model was used for analysis.43 Two rating scales were applied to this questionnaire because there were two sets of response options with different characteristics. 
Statistical Analysis
Commercial statistical software (SPSS Version 25; SPSS Science, Chicago, IL) was used to analyze the data.45 Descriptive statistical analyses were performed to characterize the participants’ sociodemographic and clinical characteristics. An unpaired t-test was used to compare means of the VILL scores among age groups, sex, two different levels of visual acuity (VA), AMD stage, and the self-reported presence of depression (“Are you known to have depression?”), to support discriminant validity of the instrument. A P value < 0.05 was considered statistically significant. 
Results
Focus Groups Discussions, in-Depth Interviews, and Cognitive Debriefs
Nineteen patients with early, intermediate, or late AMD participated in in-depth interviews. Five patients with early AMD and five patients with late AMD participated in one FGD each. Table 1 shows that both subgroups had similar demographic characteristics. 
Table 1.
 
Demographic Characteristics of In-Depth Interviews and Focus Group Discussions
Table 1.
 
Demographic Characteristics of In-Depth Interviews and Focus Group Discussions
FGDs and in-depth interviews revealed that emerging themes were related to difficulties with reading, accessing information, and recognizing people in everyday situations under low contrast and/or low lighting levels (e.g. newspaper, price tags in shops, advertisements with colorful backgrounds, and encounters outside in the dark). Activities related to mobility at dusk or at night including driving as well as safety while engaging in mobility were also mentioned frequently. Moreover, in both the interviews and the FGDs, common themes were socio-emotional distress due to the concern of losing independence, worsening vision in the future, and the resulting impact on everyday life. Based on the results of the qualitative analysis we developed a draft questionnaire consisting of 75 items with a 5-step response scale, including the domains of “reading and accessing information,” “orientation and mobility,” “safety,” and “socio-emotional well-being.” After conducting cognitive debriefing interviews with 3 patients with AMD to assess comprehensibility and appropriateness of each question, 7 items were removed because patients felt they were difficult to understand and not relevant to their daily lives, resulting in a revised version of the questionnaire with 68 items with a 5-step response scale. 
Psychometric Evaluation of the VILL Questionnaire
The pilot VILL was administered to 127 patients with early, intermediate, and late AMD and the validity, reliability, and dimensionality of the questionnaire were assessed using Rasch analysis (Table 2). One patient was excluded from the analysis because the interview was not completed. In accordance with the two response categories, two rating scales were applied (items 1–32 referring to “difficultly,” ranging from “very” to “not at all,” and items 33–68 referring to “bother,” ranging from “always” to “never”). The 68-item version of the VILL had disordered thresholds in both rating scales, suggesting that the use of the 5 initial response options was suboptimal. For both rating scales, category 1 was unlikely to be chosen. Consequently, categories 0 and 1 (“very”/“always” and “considerable”/“frequent”) were merged, which resulted in 4 final response options for each scale. The VILL displayed good discriminant ability with PSI and PR values of 4.2 and 0.95, respectively. The targeting of the VILL was slightly suboptimal with a difference in person and item means of 0.52 logits. The PCA yielded evidence of multidimensionality, because the first factor explained < 50% (47.3%) of the variance and had an eigenvalue of 5.95. This suggests the existence of a second dimension. Moreover, six items (items 39, 40, 50, 52, 64, and 86) demonstrated substantial misfit (MNSQ > 1.3). Twenty-nine items revealed floor (27 items) or ceiling effects (2 items) and for two items a large proportion of participants (> 30%) indicated that these items were not applicable. In total, 31 items were removed due to the reasons stated above and 37 items remained. For the 37-item version of the VILL, PSI and PR were 3.55 and 0.93, respectively, implying that three levels of person strata can be detected. Targeting was good, with a difference between person and item means of 0.29. The person-item map indicated a good item coverage for the majority of the sample (Figure). Six items (items 3, 8, 16, 18, 44, and 49) demonstrated misfit with MNSQ values < 0.7, however, removal of these items did not improve fit statistics. There was still evidence of multidimensionality in the PCA with the first factor explaining 44.7% of the variance and an eigenvalue of 4.5 for the first contrast, indicating the presence of at least 2 subscales. Four items (items 58, 59, 61, and 66) loaded positively (correlation > 0.4) onto the first contrast. These items referred to aspects of emotional well-being, suggesting that they belong to the same domain. Therefore, we split the items into three subsets. An emotional well-being subscale with the above-mentioned four items, a reading and accessing information subscale (20 items), and a mobility and safety subscale (13 items). More details on the items and the assignment into the subscales can be found in the Supplementary Material. The reading and mobility scales showed good PSI and PR values (2.68 and 0.88 for the reading scale and 2.03 and 0.80 for the mobility scale). However, the emotional well-being scale returned unsatisfying results regarding PSI and PR with values of 1.13 and 0.55, respectively. No item displayed misfit in the reading and mobility scale. The targeting of both scales was slightly suboptimal with a difference in person and item means of 0.88 and 0.80 logits, respectively, but within an acceptable range. The reading scale showed minimal evidence of multidimensionality with PCA for the first factor explaining > 50% (53.9%) and an eigenvalue for the first contrast of 2.6. For the mobility scale, PCA of the residuals was 54.9%, and the first contrast of the residuals was 2.7 eigenvalue, which is acceptable for the requirements of unidimensionality. No significant DIF was found for gender or age in either of the subscales. 
Table 2.
 
Fit Parameters of the VILL Questionnaire With 68 Items (VILL-68), the VILL Questionnaire Without Misfitting Items (VILL-37), the Reading Scale (20 items), the Mobility Scale (13 items) and the Emotional Scale (4 items) Compared With Rasch Model Requirements
Table 2.
 
Fit Parameters of the VILL Questionnaire With 68 Items (VILL-68), the VILL Questionnaire Without Misfitting Items (VILL-37), the Reading Scale (20 items), the Mobility Scale (13 items) and the Emotional Scale (4 items) Compared With Rasch Model Requirements
Figure.
 
Person-ITEM map for the VILL questionnaire with 37 items.
Figure.
 
Person-ITEM map for the VILL questionnaire with 37 items.
Association of the VILL Questionnaires Scores with Sample Characteristics
Rasch analysis was used to generate person measures in logits for all participants with higher scores indicating poorer VRQOL. The overall mean score was −0.28 (SD ± 0.84) logits. Mean person measures for the 3 subscale scores for different groups are shown in Table 3. The mean person measures of the overall score and two subscales (reading and accessing information, and emotional well-being) were significantly lower in participants with early/intermediate than in those with late AMD (P ≤ 0.025; see Table 3). The orientation and mobility subscale did not differ between these subgroups. There was no difference in the overall VILL scores by age groups, sex, level of visual impairment, or self-reported depression (all P values > 0.05; see Table 3). Likewise, there was no significant difference in any of the sample characteristics regarding the subscale scores for the reading and mobility subscale, although the difference between age groups in the latter one almost reached significance (P = 0.055). For the score of the emotional scale, there was a significant difference by age groups and sex, but not for visual impairment or depression. 
Table 3.
 
VILL Questionnaire Scores by Sample Characteristics, n = 126
Table 3.
 
VILL Questionnaire Scores by Sample Characteristics, n = 126
Discussion
Patients with AMD report difficulty with vision-related activities and functioning under visually challenging conditions at all stages of the disease. These include reading, social interaction/recognizing people, mobility/safety, and the socio-emotional impact of these difficulties. These aspects were considered when developing a novel PRO instrument to capture patient-reported difficulty with vision-related activities and functioning under visually challenging conditions. Using a large item pool generated with participant and expert input as well as Rasch analysis the resulting VILL questionnaire is able to discriminate among three different strata of ability and the measurement was not affected by sample characteristics, such as age, sex, or depression in our sample but captured differences between AMD disease stages. 
Many of the proposed criteria for quality of health status questionnaires, such as content validity, criterion validity, internal consistency, no floor or ceiling effects, and good interpretability, are met with the VILL-37.46 However, the 37-item version still displays multidimensionality, indicating that splitting the scale into subscales, including a reading, a mobility, and an emotional subscale, is reasonable and necessary for further psychometric evaluation in a larger sample. Persisting issues with the emotional scale could be solved by removing all four items belonging to this scale. However, this results in a lack of any information on the socio-emotional impact of AMD and would render the questionnaire a measure of functional impairment and visual difficulty only. Although there is no consensus on a definition of VRQOL, there is considerable agreement among experts that it should encompass psychological or psycho-social well-being.47,48 Therefore, the emotional subscale of the VILL was retained and requires further evaluation. None of the items in the VILL-37 exhibited significant DIF by gender or age group (< 75 / ≥ 75 years) in our sample. 
Patients with AMD, particularly those with early or intermediate stages, commonly report visual difficulties in dim light and under low contrast.4952 These common visual problems can be verified psychophysically.9,4951 Rod photoreceptors are selectively vulnerable to dysfunction and degeneration in the early stages of AMD and studies have demonstrated that patients in the early stages have, for example, impaired rod-mediated dark adaptation.5355 Focusing on this, the VILL questionnaire will be useful as a patient-centered tool for assessing VRQOL and functional impairment in patients with AMD, in particular in early and intermediate disease stages as opposed to late AMD. Person measures of the reading and emotional subscales were sensitive to disease severity in our sample. This supports the responsiveness of the VILL but it is unclear from the available data why the mobility subscale did not differ between early stages of AMD and late AMD. Patients with AMD might affect reading and near work to a larger extent than mobility but additional studies are needed to explore this in more detail. Unlike disease stage, photopic VA was not significantly associated with person measures of the VILL subscales. This corresponds with the design of the VILL items, which focus on the characteristic functional deficit under low contrast and low luminance in AMD. 
Strengths of our study include the use of qualitative research, a literature review, and expert input to create a large item pool together with patients with various stages of AMD. Therefore, items have real-world validity and are patient relevant. Item selection was informed by cognitive debriefing interviews and further pilot data. Patients were clinically assessed and uniformly staged according to current clinical reference standards. Another strength is the use of Rasch analysis and the final instrument could be shown to satisfy requirements of the Rasch model. Rasch analysis provided several useful indicators of scale category organization, such as the optimal number of response options and the validity and functioning of the rating scale.27,56,57 As a result of disordered thresholds, we collapsed the two used rating scales from five to four response options. This is in line with previous findings that ophthalmic questionnaires function optimally with no more than five and often four response categories.58 There are limitations of our study, which include the limited sample size and persisting psychometric issues, such as the poor functioning of the emotional well-being subscale as well as the age structure of the sample with a higher proportion of late AMD in older participants. At this stage in the questionnaire development, the scale was retained as this ensures that the PRO extends insights from conventional psychophysical assessments of visual functioning to the affective aspect of VRQOL in patients with AMD. Only few participants in our study had early AMD; as a consequence, the content of the items is not specific to early AMD and no conclusions regarding the reliability and validity of the VILL in a sample with only early AMD can be drawn from our data. Because the distinction of early versus intermediate AMD is solely made by structural criteria, not functional criteria, we collapsed both groups – early and intermediate AMD – into an “early stages of AMD” group. We did not assess the VILL's test-retest reliability and the association with functional measures of vision. For this as well as an evaluation of clinical utility, further evaluation of the VILL in a larger sample size is required. The VILL-37 itself is currently limited in use by its length and associated participant burden. However, the goal of this study was to design and assess psychometric characteristics of the instrument and our results support the validity of the tool for use in AMD. Additional studies will focus on further item reduction. 
In conclusion, patients with AMD report difficulty with vision-related activities and functioning under visually challenging conditions at all stages of the disease. These aspects were considered when developing the 37-item VILL, which has demonstrated good psychometric characteristics. Further assessments of reliability and validity in different studies are ongoing. 
Acknowledgments
Supported by the German Scholars Organization/Else Kröhner Fresenius Stiftung (GSO/EKFS 16) and the Jackstädt Foundation. 
Disclosure: S.G. Pondorfer, Heidelberg Engineering (F), Optos (F), Carl Zeiss MedicTec (F), CenterVue (F); J.H. Terheyden, Heidelberg Engineering (F), Optos (F), Carl Zeiss MedicTec (F), CenterVue (F); H. Overhoff, None, J. Stasch-Bouws, None, F.G. Holz, Heidelberg Engineering (F, C, R), Optos (F), Carl Zeiss MedicTec (F, C), CenterVue (F), Allergan (F, R), Alcon/Novartis (F, R), Genentech/Roche (F, R), Bayer (F, R), Acucela (F, R), Boehringer Ingelheim (F, R); R.P. Finger, Heidelberg Engineering (F), Optos (F), Carl Zeiss MedicTec (F), CenterVue (F), Bayer (C), Novartis (C), Santen (C), Opthea (C), Novelion (C), Retina Implant (C), Oxford Innovation (C), Novartis (F) 
References
Finger RP, Schmitz-Valckenberg S, Schmid M, et al. MACUSTAR: Development and clinical validation of functional, structural, and patient-reported endpoints in intermediate age-related macular degeneration. Ophthalmologica. 2019; 241: 61–72. [CrossRef] [PubMed]
Pondorfer SG, Terheyden JH, Heinemann M, Wintergerst MWM, Holz FG, Finger RP. Association of vision-related quality of life with visual function in age-related macular degeneration. Sci Rep. 2019; 9: 15326. [CrossRef] [PubMed]
Welker SG, Pfau M, Heinemann M, Schmitz-Valckenberg S, Holz FG, Finger RP. Retest reliability of mesopic and dark-adapted microperimetry in patients with intermediate age-related macular degeneration and age-matched controls. Invest Ophthalmol Vis Sci. 2018; 59: AMD152–AMD159. [CrossRef] [PubMed]
Puell MC, Barrio AR, Palomo-Alvarez C, Gomez-Sanz FJ, Clement-Corral A, Perez-Carrasco MJ. Impaired mesopic visual acuity in eyes with early age-related macular degeneration. Invest Ophthalmol Vis Sci. 2012; 53: 7310–7314. [CrossRef] [PubMed]
Cassels NK, Wild JM, Margrain TH, Chong V, Acton JH. The use of microperimetry in assessing visual function in age-related macular degeneration, Vol. 1. New York, NY: Elsevier; 2018 Jan–Feb: 40–55.
Owsley C, Huisingh C, Jackson GR, et al. Associations between abnormal rod-mediated dark adaptation and health and functioning in older adults with normal macular health. Invest Ophthalmol Vis Sci. 2014; 55: 4776–4789. [CrossRef] [PubMed]
Dimitrov PN, Robman LD, Varsamidis M, et al. Visual function tests as potential biomarkers in age-related macular degeneration. Invest Ophthalmol Vis Sci. 2011; 52: 9457–9469. [CrossRef] [PubMed]
McKeague C, Binns AM, Margrain TH. An evaluation of two candidate functional biomarkers for AMD. Optom Vis Sci. 2014; 91: 916–924. [CrossRef] [PubMed]
Owsley C, McGwin G JR, Scilley K, Kallies K. Development of a questionnaire to assess vision problems under low luminance in age-related maculopathy. Invest Ophthalmol Vis Sci. 2006; 47: 528–535. [CrossRef] [PubMed]
Chandramohan A, Stinnett SS, Petrowski JT, et al. Visual function measures in early and intermediate age-related macular degeneration. Retina (Philadelphia, Pa.). 2016; 36: 1021–1031. [CrossRef] [PubMed]
Cocce KJ, Stinnett SS, Luhmann UFO, et al. Visual function metrics in early and intermediate dry age-related macular degeneration for use as clinical trial endpoints. Am J Ophthalmol. 2018; 189: 127–138. [CrossRef] [PubMed]
Wu Z, Ayton LN, Guymer RH, Luu CD. Low-luminance visual acuity and microperimetry in age-related macular degeneration. Ophthalmology. 2014; 121: 1612–1619. [CrossRef] [PubMed]
Mackenzie PJ, Chang TS, Scott IU, et al. Assessment of vision-related function in patients with age-related macular degeneration. Ophthalmology. 2002; 109: 720–729. [CrossRef] [PubMed]
Finger RP, Fenwick E, Owsley C, Holz FG, Lamoureux EL. Visual functioning and quality of life under low luminance: evaluation of the German Low Luminance Questionnaire. Invest Ophthalmol Vis Sci. 2011; 52: 8241–8249. [CrossRef] [PubMed]
Finger RP, Fenwick E, Lamoureux EL. Impact of early and late age-related macular degeneration on quality of life. In Scholl HPN, Massof RW, West S, eds. Ophthalmology and the Ageing Society. New York, NY: Springer; 2013;181–192.
Wu Z, Guymer RH, Finger RP. Low luminance deficit and night vision symptoms in intermediate age-related macular degeneration. Br J Ophthalmol. 2016; 100: 395–398. [CrossRef] [PubMed]
Ying G-S, Maguire MG, Liu C, Antoszyk AN, Macular CAR. Night vision symptoms and progression of age-related macular degeneration in the complications of age-related macular degeneration prevention trial. Ophthalmology. 2008; 115: 1876–1882. [CrossRef] [PubMed]
Ying G-S, Maguire MG. Development of a risk score for geographic atrophy in complications of the age-related macular degeneration prevention trial. Ophthalmology. 2011; 118: 332–338. [CrossRef] [PubMed]
McGuinness MB, Finger RP, Wu Z, et al. Properties of the impact of vision impairment and night vision questionnaires among people with intermediate age-related macular degeneration. Transl Vis Sci Technol. 2019; 8: 3. [CrossRef]
Prem Senthil M, Khadka J, Pesudovs K. Assessment of patient-reported outcomes in retinal diseases: a systematic review. Vol. 4. New York, NY: Elsevier; 2017: 546–582.
Black N. Patient reported outcome measures could help transform healthcare. BMJ (Clinical Research Ed.). 2013; 346: f167. [PubMed]
McGuinness MB, Finger RP, Wu Z, et al. Properties of the impact of vision impairment and night vision questionnaires among people with intermediate age-related macular degeneration. Transl Vis Sci Technol. 2019; 8: 3. [CrossRef]
US Food and Drug Administration Centre for Drug Evaluation and Research. Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims. Guidance for Industry. 2009. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-reported-outcome-measures-use-medical-product-development-support-labeling-claims.
Ferris FL, Wilkinson CP, Bird A, et al. Clinical classification of age-related macular degeneration. Ophthalmology. 2013; 120: 844–851. [CrossRef] [PubMed]
Kimel M, Leidy NK, Tschosik E, et al. Functional Reading Independence (FRI) Index: a new patient-reported outcome measure for patients with geographic atrophy. Invest Ophthalmol Vis Sci. 2016; 57: 6298–6304. [CrossRef] [PubMed]
Finger RP, Tellis B, Crewe J, Keeffe JE, Ayton LN, Guymer RH. Developing the impact of Vision Impairment-Very Low Vision (IVI-VLV) questionnaire as part of the LoVADA protocol. Invest Ophthalmol Vis Sci. 2014; 55: 6150–6158. [CrossRef] [PubMed]
Mangione CM, Lee PP, Gutierrez PR, Spritzer K, Berry S, Hays RD. Development of the 25-item National Eye Institute Visual Function Questionnaire. Arch Ophthalmol. 2001; 119: 1050–1058. [CrossRef] [PubMed]
Elliot TR, Rivera P, Tucker E. Handbook of Group Counseling and Psychotherapy: Groups in behavioral health and medical settings. New York: Sage; 2004: 338–350.
QSR International (2017). NVivo Qualitative Data Analysis Software [Software]. Available from https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/home.
Patrick DL, Burke LB, Gwaltney CJ, et al. Content validity–establishing and reporting the evidence in newly developed patient-reported outcomes (PRO) instruments for medical product evaluation: ISPOR PRO Good Research Practices Task Force report: part 2–assessing respondent understanding. Value Health. 2011; 14: 978–988. [CrossRef] [PubMed]
Ferris FL, Kassoff A, Bresnick GH, Bailey I. New visual acuity charts for clinical research. Am J Ophthalmol. 1982; 94: 91–96. [CrossRef] [PubMed]
Lamoureux EL, Pallant JF, Pesudovs K, Rees G, Hassell JB, Keeffe JE. The impact of vision impairment questionnaire: an assessment of its domain structure using confirmatory factor analysis and Rasch analysis. Invest Ophthalmol Vis Sci. 2007; 48: 1001–1006. [CrossRef] [PubMed]
Boone WJ, Staver JR, Yale MS. Rasch Analysis in the Human Sciences. New York, NY: Springer; 2014.
Rasch G . Probabilistic Models for Some Intelligence and Attainment Tests. Chicago, IL: University of Chicago.
Wright BD, Linacre JM. Observations are always ordinal; measurements, however, must be interval. Arch Phys MedRehab. 1989; 70: 857–860.
Finger RP, McSweeney SC, Deverell L, et al. Developing an instrumental activities of daily living tool as part of the low vision assessment of daily activities protocol. Invest Ophthalmol Vis Sci. 2014; 55: 8458–8466. [CrossRef] [PubMed]
Finger RP, Kortuem K, Fenwick E, von Livonius B, Keeffe JE, Hirneiss CW. Evaluation of a vision-related utility instrument: the German vision and quality of life index. Invest Ophthalmol Vis Sci. 2013; 54: 1289–1294. [CrossRef] [PubMed]
Bond T, Fox CM. Applying the Rasch Model: Fundamental Measurement in the Human Sciences. New York, NY: Routledge; 2015.
Finger RP, Fenwick E, Marella M, et al. The impact of vision impairment on vision-specific quality of life in Germany. Invest Ophthalmol Vis Sci. 2011; 52: 3613–3619. [CrossRef] [PubMed]
Mallinson T. Why measurement matters for measuring patient vision outcomes. Optom Vis Sci. 2007; 84: 675–682. [CrossRef] [PubMed]
Linacre JM . WINSTEPS Rasch measurement computer program. Chicago, IL: Winsteps.com; 2016.
Linacre JM . A User's guide to Winsteps/Ministeps Rasch-Model Programs. Chicago, IL: MESA Press; 2006.
Pesudovs K, Burr JM, Harley C, Elliott DB. The development, assessment, and selection of questionnaires. Optom Vis Sci. 2007; 84: 663–674. [CrossRef] [PubMed]
IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.
Terwee CB, Bot SDM, de Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007; 60: 34–42. [CrossRef] [PubMed]
Bonomi AE, Patrick DL, Bushnell DM, Martin M. Validation of the United States' version of the World Health Organization Quality of Life (WHOQOL) instrument. J Clin Epidemiol. 2000; 53: 1–12. [CrossRef] [PubMed]
Aaronson NK. Quality of life: what is it? How should it be measured? Oncology (Williston Park, N.Y.). 1988; 2: 69–76, 64. [PubMed]
Scilley K, Jackson GR, Cideciyan AV, Maguire MG, Jacobson SG, Owsley C. Early age-related maculopathy and self-reported visual difficulty in daily life. Ophthalmology. 2002; 109: 1235–1242. [CrossRef] [PubMed]
Steinmetz RL, Haimovici R, Jubb C, Fitzke FW, Bird AC. Symptomatic abnormalities of dark adaptation in patients with age-related Bruch's membrane change. Br J Ophthalmol. 1993; 77: 549–554. [CrossRef] [PubMed]
Owsley C, Jackson GR, Cideciyan AV, et al. Psychophysical evidence for rod vulnerability in age-related macular degeneration. Invest Ophthalmol Vis Sci. 2000; 41: 267–273. [PubMed]
Owsley C, Jackson GR, White M, Feist R, Edwards D. Delays in rod-mediated dark adaptation in early age-related maculopathy. Ophthalmology. 2001; 108: 1196–1202. [CrossRef] [PubMed]
Jackson GR, Owsley C, Curcio CA. Photoreceptor degeneration and dysfunction in aging and age-related maculopathy. Ageing Res Rev. 2002; 1: 381–396. [CrossRef] [PubMed]
Owsley C, McGwin G JR, Clark ME, et al. Delayed rod-mediated dark adaptation is a functional biomarker for incident early age-related macular degeneration. Ophthalmology. 2016; 123: 344–351. [CrossRef] [PubMed]
Curcio CA, Medeiros NE, Millican CL. Photoreceptor loss in age-related macular degeneration. Invest Ophthalmol Vis Sci. 1996; 37(7): 1236–1249. [PubMed]
Pesudovs K, Noble BA. Improving subjective scaling of pain using Rasch analysis. J Pain. 2005; 6: 630–636. [CrossRef] [PubMed]
Likert R . A technique for the measurement of attitudes. Arch Psychol. 1932; 22(140): 55.
Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Multiplicative rating scales do not enable measurement of vision-related quality of life. Clin Exp Optom. 2011; 94: 52–62. [CrossRef] [PubMed]
Figure.
 
Person-ITEM map for the VILL questionnaire with 37 items.
Figure.
 
Person-ITEM map for the VILL questionnaire with 37 items.
Table 1.
 
Demographic Characteristics of In-Depth Interviews and Focus Group Discussions
Table 1.
 
Demographic Characteristics of In-Depth Interviews and Focus Group Discussions
Table 2.
 
Fit Parameters of the VILL Questionnaire With 68 Items (VILL-68), the VILL Questionnaire Without Misfitting Items (VILL-37), the Reading Scale (20 items), the Mobility Scale (13 items) and the Emotional Scale (4 items) Compared With Rasch Model Requirements
Table 2.
 
Fit Parameters of the VILL Questionnaire With 68 Items (VILL-68), the VILL Questionnaire Without Misfitting Items (VILL-37), the Reading Scale (20 items), the Mobility Scale (13 items) and the Emotional Scale (4 items) Compared With Rasch Model Requirements
Table 3.
 
VILL Questionnaire Scores by Sample Characteristics, n = 126
Table 3.
 
VILL Questionnaire Scores by Sample Characteristics, n = 126
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×